Why the study?
Does an automatic ECG compression methodology based on noise estimation and wavelet domain coding improve ECG reconstruction and visual quality?
Does an automatic ECG compression methodology based on noise estimation and wavelet domain coding improve ECG reconstruction and visual quality?
A novel ECG compression methodology based on noise estimation and wavelet coding maintains high reconstruction quality and enhances visual quality for clinical interpretation.
May support ECG compression in bandwidth-limited settings; leaves open prospective clinical validation before routine adoption.
This paper introduces a new methodology for compressing ECG signals in an automatic way guaranteeing signal interpretation quality. The approach is based on noise estimation in the ECG signal that is used as a compression threshold in the coding stage. The Set Partitioning in Hierarchical Trees algorithm is used to code the signal in the wavelet domain. Forty different ECG records from two different ECG databases commonly used in ECG compression have been considered to validate the approach. Three cardiologists have participated in the clinical trial using mean opinion score tests in order to rate the signals quality. Results showed that the approach not only achieves very good ECG reconstruction quality but also enhances the visual quality of the ECG signal.
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Alesanco et al. (2008) studied this question.
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